A modular AI ecosystem focused on frame-based image generation, training, and visualization.
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Training
FrameForge
AI training, dataset preparation, and orchestration within the Frame ecosystem. -
Viewing
FrameView
Visualization, inspection, and analysis of generated frames and training results. -
Generating
FrameCreate
Generative image AI of the Frame ecosystem.
Work in Progress
FrameView is a focused, high‑volume gallery for AI images.
Drop your folders, reindex, and browse with clean tags, categories, and full metadata.
FrameView is designed for fictional, stylized, and synthetic content.
Use on real individuals without consent is explicitly discouraged.
- Local‑first gallery: scans folders recursively and builds a fast index
- Metadata aware: reads prompts and generation settings from PNG text chunks
- Auto categories: the first prompt tag becomes a category
- Filters: tags, categories, model, LoRA, and search
- Detail view: large preview + full metadata
- Reindex on demand from the Settings screen
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Put images into:
images/(subfolders are supported)
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Open the UI:
http://<your-host>:4173
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Click Settings → Reindex after adding new images
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Install dependencies:
npm install
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Edit environment values:
.env.example→.env
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Set up database (Postgres):
sudo ./scripts/setup_db.sh
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Build services:
npm run build
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Start services (systemd):
sudo ./scripts/setup_systemd.shServices created:frameview-api.serviceframeview-ui.serviceframeview-indexer.serviceframeview-indexer.path
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Open the UI:
http://<your-host>:4173
- Tags are derived from
raw_prompt(score tokens are ignored). - Categories are auto‑generated from the first prompt tag.
- Use the top navigation to switch between Gallery, Tags & Categories, and Settings.
- Side note: FrameView currently reads prompt tags only. Flux‑style prompts are not parsed.
services/indexer→ scans and ingests metadataservices/api→ search/filter APIservices/ui→ React gallery
MIT